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Visibility restoration of haze and dust image using color correction and composite channel prior

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Abstract

Visibility restoration of images under haze and dust weather is essential in computer vision tasks. In this work, an algorithm for image visibility restoration based on color correction and composite channel prior (CCP) is proposed. First, the color of a dust image is corrected by color compensation and white balance for blue and red channels. Haze and dust images are effectively distinguished by channel differences. Secondly, the composite channels are defined by simple multiplication and subtraction, and the composite channels of haze image and clear image have a very close pixel distribution. Then, according to atmospheric imaging rules, haze is the main factor that causes brightness difference of each composite channel. To eliminate the brightness difference, an adaptive gamma correction function based on haze density is proposed. In addition, as another important parameter of image restoration task, mean inequality and morphological operations are used to obtain more accurate mid-channel atmospheric light. Finally, a practical transmission map and high-quality clear image are obtained by atmospheric scattering models. Experimental results show that the proposed method is usable and practical. Our results have rich details and edges, especially for dust images.

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Authors and Affiliations

  1. School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou, Gansu, China

    Yang Yan, Zhang Jinlong, Liu Ce, Zhang Haowen & Li Xiang

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  1. Yang Yan
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  2. Zhang Jinlong
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  3. Liu Ce
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  4. Zhang Haowen
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  5. Li Xiang
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Correspondence to Yang Yan.

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Yan, Y., Jinlong, Z., Ce, L. et al. Visibility restoration of haze and dust image using color correction and composite channel prior. Vis Comput 39, 2795–2809 (2023). https://doi.org/10.1007/s00371-022-02493-3

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